imanoop7 / llm_for_coding

LLM for Coding

Welcome to the LLM for Coding repository, where we harness the power of large language models (LLMs) to enhance coding experiences. This repository contains Jupyter notebooks that interface with state-of-the-art code generation models.

Notebooks

• code_llama.ipynb: Utilizes the CodeLlama-13B-Instruct-fp16 model for generating code with a focus on following instructions closely.
• code_with_gemma.ipynb: Leverages the codegemma-2b model, optimized for generating high-quality code snippets.
• code_llama-3.ipynb: Employs the llama-3 model, designed for versatile code generation across various programming languages.

Getting Started

To use these notebooks:

1. Ensure you have Jupyter installed. If not, install it using:

   pip install jupyter

2. Clone this repository:

   git clone [email protected]:imanoop7//llm_for_coding.git

3. Navigate to the cloned directory and start Jupyter: cd llm_for_coding 4.Open the desired notebook and follow the instructions within to start coding with the power of LLMs. Prerequisites Python 3.8+ Jupyter Notebook Internet connection (for model access) Models Here’s a brief overview of the models used in our notebooks:

• CodeLlama-13B-Instruct-fp16: A 13-billion parameter model fine-tuned for following specific coding instructions.
• codegemma-2b: A 2-billion parameter model that excels in generating concise and accurate code.
• llama-3: A versatile model capable of understanding and generating code in multiple programming languages. ##Contributing Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag “enhancement”.

Don’t forget to give the project a star! Thanks again!

License

Distributed under the MIT License. See LICENSE for more information.